Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources

Kevin Malena, Christopher Link, Sven Mertin, Sandra Gausemeier, Ansgar Trächtler, Ansgar Trächtler

Abstract

The online fitting of a microscopic traffic simulation model to reconstruct the current state of a real traffic area can be challenging depending on the provided data. This paper presents a novel method based on limited data from sensors positioned at specific locations and guarantees a general accordance of reality and simulation in terms of multimodal road traffic counts and vehicle speeds. In these considerations, the actual purpose of research is of particular importance. Here, the research aims at improving the traffic flow by controlling the Traffic Light Systems (TLS) of the examined area which is why the current traffic state and the route choices of individual road users are the matter of interest. An integer optimization problem is derived to fit the current simulation to the latest field measurements. The concept can be transferred to any road traffic network and results in an observation of the current multimodal traffic state matching at the given sensor position. First case studies show promosing results in terms of deviations between reality and simulation.

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Paper Citation


in Harvard Style

Malena K., Link C., Mertin S., Gausemeier S. and Trächtler A. (2021). Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources. In Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-513-5, pages 386-395. DOI: 10.5220/0010414903860395


in Bibtex Style

@conference{vehits21,
author={Kevin Malena and Christopher Link and Sven Mertin and Sandra Gausemeier and Ansgar Trächtler},
title={Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources},
booktitle={Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2021},
pages={386-395},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010414903860395},
isbn={978-989-758-513-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources
SN - 978-989-758-513-5
AU - Malena K.
AU - Link C.
AU - Mertin S.
AU - Gausemeier S.
AU - Trächtler A.
PY - 2021
SP - 386
EP - 395
DO - 10.5220/0010414903860395